Model comparison
GLM-5.1 vs GPT-5.3 Codex
GLM-5.1 is the stronger model overall, scoring 47.8 to 45.8 on the Noometry Index.
Last verified . 6 shared benchmarks.
Summary
- They share 6 benchmarks with published results for both. GLM-5.1 scores higher in 1 category and GPT-5.3 Codex in 1 category; one gap is clear of the uncertainty.
- The widest gap is in agentic & tool use, where GPT-5.3 Codex leads 48.0 to 24.9.
- The biggest single-benchmark swing is WeirdML: 57.1% for GLM-5.1 and 79.3% for GPT-5.3 Codex.
- GLM-5.1 is cheaper at $1.40 / $4.40 per million input/output tokens, against $1.75 / $14 for GPT-5.3 Codex.
- GPT-5.3 Codex accepts more context: 400K tokens versus 200K.
- GLM-5.1 has downloadable open weights; the other is API-only.
Side by side
| GLM-5.1 | GPT-5.3 Codex | |
|---|---|---|
| Provider | Z.ai (Zhipu) | OpenAI |
| Noometry Index | 47.8 | 45.8 |
| Released | 2026-04-07 | 2026-02-05 |
| Weights | Open | Proprietary |
| Context window | 200K | 400K |
| Max output | 131K | 128K |
| Input $ / M tokens | $1.40 | $1.75 |
| Output $ / M tokens | $4.40 | $14 |
| Results tracked | 41 | 8 |
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Category by category
Coding Too close to call
GLM-5.1: 48.7 (#55), GPT-5.3 Codex: 48.6 (#56)
| Benchmark | GLM-5.1 | GPT-5.3 Codex |
|---|---|---|
| SWE-bench Verified | 74.2% | 74.8% |
| LMArena WebDev | 1508 | 1409 |
| WeirdML | 57.1% | 79.3% |
| ALE-Bench | 887.1 | 1,655 |
| SciCode | 43.8% | — |
| LMArena Coding | 1485 | — |
Agentic & Tool Use GPT-5.3 Codex leads
GLM-5.1: 24.9 (#113), GPT-5.3 Codex: 48.0 (#9)
| Benchmark | GLM-5.1 | GPT-5.3 Codex |
|---|---|---|
| Vending-Bench 2 | 5,634 | 5,940 |
| Terminal-Bench | — | 78.4% |
| APEX-Agents | 40.9% | — |
| ExploitBench | 18.1% | — |
| GBAEval | 0% | — |
| METR Time Horizons | — | 74.5% |
Reasoning Not comparable
GLM-5.1: 39.1 (#60), GPT-5.3 Codex: —
| Benchmark | GLM-5.1 | GPT-5.3 Codex |
|---|---|---|
| Epoch Capabilities Index | 149.84 | 156.77 |
| SimpleBench | 55.1% | — |
| NYT Connections (extended) | 77.7% | — |
| CritPt | 4.6% | — |
| Chess Puzzles | 19% | — |
| Thematic Generalization | 69.8% | — |
| LMArena Hard Prompts | 1472 | — |
Math Not comparable
GLM-5.1: 49.7 (#60), GPT-5.3 Codex: —
| Benchmark | GLM-5.1 | GPT-5.3 Codex |
|---|---|---|
| FrontierMath (Tiers 1-3) | 36.8% | — |
| MathArena Final-Answer Competitions | 67.1% | — |
| OTIS Mock AIME 2024-2025 | 93.3% | — |
| ProofBench | 22.2% | — |
| LMArena Math | 1473 | — |
| FrontierMath (Feb 2025 set) | 33.4% | — |
| FrontierMath Tier 4 (v1) | 12.5% | — |
Knowledge Not comparable
GLM-5.1: 54.9 (#50), GPT-5.3 Codex: —
| Benchmark | GLM-5.1 | GPT-5.3 Codex |
|---|---|---|
| GPQA Diamond | 89.9% | — |
| SimpleQA Verified | 34% | — |
| LMArena Expert | 1476 | — |
Multilingual Not comparable
GLM-5.1: 55.0 (#36), GPT-5.3 Codex: —
| Benchmark | GLM-5.1 | GPT-5.3 Codex |
|---|---|---|
| LMArena Non-English | 1447 | — |
| LMArena Chinese | 1515 | — |
| LMArena French | 1474 | — |
| LMArena German | 1465 | — |
| LMArena Japanese | 1434 | — |
| LMArena Korean | 1418 | — |
| LMArena Russian | 1454 | — |
| LMArena Spanish | 1469 | — |
Instruction Following Not comparable
GLM-5.1: 76.3 (#42), GPT-5.3 Codex: —
| Benchmark | GLM-5.1 | GPT-5.3 Codex |
|---|---|---|
| LMArena Instruction Following | 1451 | — |
Long Context Not comparable
GLM-5.1: 44.9 (#53), GPT-5.3 Codex: —
| Benchmark | GLM-5.1 | GPT-5.3 Codex |
|---|---|---|
| LMArena Longer Query | 1466 | — |
Writing & Preference Not comparable
GLM-5.1: 66.9 (#31), GPT-5.3 Codex: —
| Benchmark | GLM-5.1 | GPT-5.3 Codex |
|---|---|---|
| LMArena Text | 1461 | — |
| LMArena Creative Writing | 1453 | — |
| EQ-Bench Creative Writing | 1592 | — |
| LMArena Multi-Turn | 1472 | — |
Frequently asked questions
Is GLM-5.1 better than GPT-5.3 Codex?
GLM-5.1 is the stronger model overall, scoring 47.8 to 45.8 on the Noometry Index.
Which is cheaper, GLM-5.1 or GPT-5.3 Codex?
GLM-5.1 is cheaper. It lists at $1.40 per million input tokens and $4.40 per million output tokens; GPT-5.3 Codex lists at $1.75 and $14.
Is GLM-5.1 or GPT-5.3 Codex better for coding?
They score almost the same on coding (48.7 vs 48.6); test both on your own repository before choosing.
Which has the bigger context window?
GPT-5.3 Codex does, with 400K tokens against 200K.
How many benchmarks do GLM-5.1 and GPT-5.3 Codex share?
6 benchmarks have published results for both models. GLM-5.1 has 41 scored results on Noometry and GPT-5.3 Codex has 8.